Image processing method for facilitating data transmission

ABSTRACT

An image processing method for facilitating data transmission is provided. An image compression method is performed to convert X-bits binary digital signals to a binary compressed data in the form of n*2 m , in which n is represented by the former Y bits of the X-bits binary digital signals, m is set to the value of (X−Y), and represented by binary numbers with [log 2 (X−Y+1)] bits. The binary compressed data is transmitted with a sequence of [log 2 (X−Y+1)]+Y bits, representing (m, n), wherein m is the former [log 2 (X−Y+1)] bits and n is the latter Y bits. Therefore, by the present image compression method, the transmission amount of image data is reduced. The transmission time of image data and the volume of a memory for storing the image data are also reduced.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image processing method, and moreparticularly, to an image compression method for binary digital signals.

2. Description of the Prior Art

Without image compression, the transmission of images requires anunacceptable bandwidth in many applications. As a result, methods ofcompressing images have been the subject of numerous researchpublications. Image compression schemes convert an image consisting of atwo-dimensional array of pixels into a sequence of bits, which are to betransmitted over a communication link. Each pixel represents theintensity of the image at a particular location therein. Thetransmission link may be an ordinary telephone line.

Consider an image comprising a gray-scale representation of a photographat a resolution of 1000×1000 lines. Each pixel typically consists of 8bits, which are used to encode 256 possible intensity levels at thecorresponding point on the photograph. Hence, without compression,transmission of the photograph requires that 8 million bits be sent overthe communication link. A typical telephone line is capable oftransmitting about 9600 bits per second; hence the picture transmissionwould require more than 10 minutes. Transmission times of this magnitudeare unacceptable.

As a result, image compression systems are needed to reduce thetransmission time. It will also be apparent to those skilled in the artthat image compression systems may also be advantageously employed inimage storage systems to reduce the amount of memory needed to store oneor more images.

Image compression involves transforming the image to a form, which canbe represented in fewer bits without losing the essential features ofthe original images. The transformed image is then transmitted over thecommunication link and the inverse transformation is applied at thereceiver to recover the image. The compression of an image typicallyrequires two steps. In the first step, the image is transformed to a newrepresentation in which the correlation between adjacent pixels isreduced. This transformation is usually completely reversible, that is,no information is lost at this stage. The number of bits of data neededto represent the transformed image is at least as large as that neededto represent the original image. The purpose of this transformation isto provide an image representation, which is more ideally suited toknown compression methods.

In the second step, referred to as quantization, each pixel in thetransformed image is replaced by a value, which is represented in fewerbits, on average, than the original pixel value. In general, theoriginal gray scale is replaced by a new scale, which has coarser stepsand hence can be represented in fewer bits. The new gray scale iscalculated from the statistical distribution of the pixel values in thetransformed image.

The quantized image resulting from the above two steps is often furthercoded for transmission over the communication link. This coding iscompletely reversible. Its purpose is to provide a more compactrepresentation of the quantized picture. At the other end of thecommunication link, the coded image is decoded, the quantizationtransformation is reversed and the inverse of the first transformationis performed on the resulting image to provide a reconstructed image.

However, the known image compression method usually utilizes acomplicated encoding and decoding circuitry to attain the more compactimage data for transmission. The coding/decoding process is alsocomplicated. Moreover, the image transformation circuitry is asignificant cost factor in image compression apparatuses. The requiredcomputational expense clearly depends on the image transformationselected. Hence, an image compression method, which requires lesscomputation than the prior image compression method, would beadvantageous.

SUMMARY OF THE INVENTION

It is one objective of the present invention to provide an imageprocessing method for facilitating data transmission, which performs animage compression method for converting X-bits binary digital signals toa binary compressed data in the form of n*2^(m), in which n isrepresented by the former Y bits of the X-bits binary digital signals, mis set to (X−Y), and represented with [log₂(X−Y+1)] bits, such that thebinary compressed data can be transmitted with a sequence of[log₂(X−Y+1)] bits, representing (m, n), wherein m is the former[log₂(X−Y+1)] bits and n is the latter Y bits. Therefore, thetransmission amount of image data is reduced, and the transmission rateof the image data is facilitated.

It is another objective of the present invention to provide an imageprocessing method for facilitating data transmission, which implements asimple compression method to convert X-bits binary digital signals to abinary compressed data in the form of n*2^(m). The complicated encodingand decoding processes for image compression and processing circuitstherefore are omitted by the present compression method.

It is a further objective of the present invention to provide an imageprocessing method, which performs a bit-enhanced technology tocompensate decompressed image data to increase the accuracy of therecovery of the image data.

In order to achieve the above objectives of this invention, the presentinvention provides an image processing method for facilitating datatransmission. The present method comprises capturing an image signalfrom an object with an image capture device, and providing the imagesignal to an analog-to-digital converter for converting the image signalto X-bits binary digital signals, wherein X is a natural number. Then,the X-bits binary digital signals is transmitted to image processingmeans for compressing the X-bits binary digital signals to a binarycompressed data in the form of n*2^(m), wherein X bits includes bit(X−1) to bit 0, m is a non-negative integer; when n is represented bythe former Y bits of the X-bits binary digital signals, Y is a naturalnumber, m is set to (X−Y), and then m is represented by binary numberswith [log₂(X−Y+1)] bits. Accordingly, the X-bits binary digital signalsare converted to the binary compressed data represented by (m, n) with asequence of [log₂(X−Y−1)]+Y bits, wherein m is the former [log₂(X−Y+1)]bits and n is the latter Y bits. The binary compressed data representedby (m, n) with the sequence of [log₂(X−Y+1)]+Y bits is then transmittedto memory means for storage. By the present image compression method,the transmission amount of image data is reduced. The transmission rateof image data is facilitated and the volume of a memory for storing theimage data is also reduced.

BRIEF DESCRIPTION OF THE DRAWINGS

The objectives and features of the present invention as well asadvantages thereof will become apparent from the following detaileddescription, considered in conjunction with the accompanying drawings.

FIG. 1 is a block diagram of an image processing system implementingimage compression methods of the present invention;

FIG. 2 is a block diagram of another image processing systemimplementing the image compression methods of the present invention;

FIG. 3 is a flow chart of a first embodiment of the present inventionillustrating the present image compression method;

FIG. 4 is a flow chart of a second embodiment of the present inventionillustrating the present image compression method;

FIG. 5 is a flow chart for illustrating an image decompression processof the present invention;

FIG. 6 is a flow chart for illustrating another image decompressionprocess of the present invention; and

FIG. 7 is a table I listing 8-bits binary image data, and 7-bits binarycompressed data and recovered image data thereof.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring to the figures, exemplary embodiments of the invention willnow be described. The exemplary embodiments are provided to illustrateaspects of the invention and should not be construed as limiting thescope of the invention. The exemplary embodiments are primarilydescribed with reference to block diagrams and flowcharts.

FIG. 1 is a block diagram of an image processing system implementingimage compression methods of the present invention, and FIG. 2 is ablock diagram of another image processing system implementing the imagecompression methods of the present invention. FIG. 3 is a flow chart ofa first embodiment of the present invention illustrating the presentimage compression method. FIG. 4 is a flow chart of a second embodimentof the present invention illustrating the present image compressionmethod. FIG. 5 is a flow chart for illustrating an image decompressionprocess of the present invention, and FIG. 6 is a flow chart forillustrating another image decompression process of the presentinvention. FIG. 7 is a table I listing 8-bits binary image data, and7-bits binary compressed data and recovered image data thereof.

Initially, referring to FIG. 1, an image is captured from an object byan image capture device 101, e.g. charge-coupled device (CCD), CMOSsensor and the like capable of converting an image signal to an electricsignal. The image signal represents intensity of a pixel of the imagecaptured by the image capture device 101. The electric signal is thenprovided to an A/D converter (analog-to-digital converter) 102 toconvert to X-bits binary digital signals, which are consisted of binaryvalues from bit (X−1) to bit 0. The X-bits binary digital signals aretransmitted to image processing means 103, e.g. an image processingcircuit, for being compressed to a binary compressed data in the form ofn*2^(m). N is represented by the former Y bits of the X-bits binarydigital signals, Y is a natural number, and m is set to (X−Y) andrepresented by binary numbers with [log₂(X−Y+1)] bits. Hence, by imageprocessing means 103, the X-bits binary digital signals are converted tothe binary compressed data represented by (m, n) with a sequence of[log₂(X−Y+1)]+Y bits, wherein m is the former [log₂(X−Y+1)] bits and nis the latter Y bits. The binary compressed data is then transmittedwith a set of binary values consisted of the sequence of [log₂(X−Y+1)]+Ybits, (x x . . . , x), to a memory 104, e.g. a buffer memory, forstorage.

FIG. 3 is a flow chart of a first embodiment of the present inventionillustrating the image compression process implemented by imageprocessing means 103. The image compression process of the firstembodiment will be described in detail in the following. In step 303,the X-bits binary digital signals consisted of binary values from bit(X−1) to bit 0 is provided to image processing means 103. The X-bitsbinary digital signals are converted to the binary compressed data inthe form of n*2^(m), wherein n is represented by the former Y bits ofthe X-bits binary digital signals. Following, in step 304, when bit(X−1) is logic level “1”, n is represented by the former bit (X−1) tobit (X−Y) of the X-bits binary digital signals, m is set to (X−Y) andrepresented by binary numbers with [log₂(X−Y+1)] bits, as step 305. Thebinary compressed data is then outputted by (m, n) with the sequence of[log₂(X−Y+1)]+Y bits, as step 314, wherein m is represented by theformer [log₂(X−Y+1)] bits and n is the latter bits consisted of bit(X−1) to bit (X−Y). In step 306, when bit (X−1) is logic level “0” andbit (X−2) is logic level “1”, n is represented by the former bit (X−2)to bit (X−1−Y) of the X-bits binary digital signals, m is set to (X−1−Y)and is represented by binary numbers with [log₂(X−Y+1)] bits, as step307. The binary compressed data is then outputted by (m, n) with[log₂(X−Y+1)]+Y bits, as step 314, wherein m is represented by theformer [log₂(X−Y+1)] bits and n is the latter bits consisted of bit(X−2) to bit (X−1−Y). In step 308, when bit (X−1) and bit (X−2) arelogic level “0”, and bit (X−3) is logic level “1”, n is represented bythe former bit (X−3) to bit (X−2−Y) of the X-bits binary digitalsignals, m is set to (X−2−Y) and is represented by binary numbers with[log₂(X−Y+1)] bits, as step 309. The binary compressed data is thenoutputted by (m, n) with [log₂(X−Y+1)]+Y bits, wherein m is representedby the former [log₂(X−Y+1)] bits and n is the latter bits consisted ofbit (X−3) to bit (X−2−Y), as step 314.

Several similar data processing steps are performed until step 310, wheneach of bit (X−1) to bit (Y+1) is logic level “0” and bit Y is logiclevel “1”, n is represented by bit Y to bit 1, m is set to 1 and isrepresented by binary digital numbers with [log₂(X−Y+1)] bits, as step311. The binary compressed data is then outputted by (m, n) with[log₂(X−Y+1)]+Y bits, wherein m is represented by the former[log₂(X−Y+1)] bits and n is the latter bits consisted of bit Y to bit 1,as step 314. In step 312, when each of bit (X−1) to bit Y is logic level“0” and bit (Y−1) is logic level “1”, n is represented by bit (Y−1) tobit 0, m is set to 0 and is represented by binary numbers with[log₂(X−Y+1)] bits, (00). The binary compressed data is then outputtedby (m, n) with [log₂(X−Y+1)]+Y bits, wherein m is represented by theformer [log₂(X−Y+1)] bits and n is the latter bits consisted of bit Y−1to bit 0, as step 314.

FIG. 7 is a table I, listing 8-bits binary digital signals consisted ofbit 7 to bit 0, and 7-bits binary compressed data and the recoveredimage data thereof. The 7-bits binary compressed data in table I aregenerated from the compression method according to the first embodiment,illustrated in FIG. 3, in which n is represented by the former 5 bits ofthe 8-bits binary digital signals, i.e. bit 7 to bit 3, and m is set toa value of 8−5=3, represented by [log₂(8−5+1)] bits, i.e. two bits. The7-bits binary compressed data is represented by seven binary values “x xx x x x x”. The former two binary values “x x” represent the value of m,and the latter five binary values “x x x x x” represent n. However, thepresent compression method is also suited to compress binary digitalsignals consisted of 10-bits, 12-bits and 16-bits, etc. And, n isdetermined according to quality of the image desired.

Referring to FIG. 1 again, the binary compressed data stored in thememory 104 is then outputted to a host 105 for further processing, suchas decompressing to recover the original image data and print out. Onedecompression method of the present invention implemented in the host105 is illustrated in FIG. 5. In step 501, the binary compressed data inthe form of n*2^(m) represented by (m, n) with [log₂(X−Y+1)]+Y bits areoutputted to the host 105 from the memory 104. In step 502, the former[log₂(X−Y+1)] bits of the binary compressed data are assigned to m,thereby obtaining the value of m, and the latter Y bits of the binarycompressed data are assigned to n. In step 503, based on the compressionalgorithm n*2^(m), binary values of n and the value of m, the binarycompressed data is decompressed to recover to the X-bits binary digitalsignals.

As shown in table I of FIG. 7, the higher the grayscale level of thepixel is, the higher the distortion of the recovered image data is.Thus, another decompression method of the present invention utilizing abit-enhanced technology (BET) is provided to compensate loss of therecovered image data, which is illustrated in FIG. 6, in which, step 601to step 603 are the same with step 501 to step 503 of FIG. 5. When m isa positive integer, as step 604, a bit-enhanced method is applied to therecovered image data. In step 605, the bit-enhanced method comprisessteps of (a) calculating a first average of a plurality of neighboringpixels around the pixel to be compensated; and (b) calculating a secondaverage of the first average and the pixel. As a result, the compensateddata of the pixel is obtained.

In accordance with the compressed method of FIG. 3, 8-bits binarydigital signals are compressed to 7-bits binary compressed data, 10-bitsbinary digital signals are compressed to 9-bits binary compressed data,12-bits binary digital signals are compressed to 11 bits binarycompressed data, and 16-bits binary digital signals are compressed to15-bits binary compressed data. Hence, transmission amount of the imagedata transmitted to the memory 104 and the host 105 is reduced. Thetransmission time of the image data is thus decreased, and the volume ofthe memory 104 for storing the image data is also reduced.

FIG. 4 is a flow chart of another image compression method according toa second embodiment of the present invention. In step 401, the X-bitsbinary digital signals consisted of binary values from bit (X−1) to bit0 is provided to image processing means 103. In step 402, based on amapping table, the X-bits binary digital signals are mapped to a binarycompressed data represented by (m, n) with [[log₂(X−Y+1)]+Y]-bits binarynumbers, in which m is represented by the former [log₂(X−Y+1) bits and nis represented by the latter Y bits. The mapping table is generatedaccording to the compression algorithm n*2^(m), wherein n is representedby the former Y bits of the X-bits binary digital signals, m is set to(X−Y) and represented by binary numbers with [log₂(X−Y+1)] bits. In step403, the binary compressed data is then transmitted to the memory 104for storage.

FIG. 2 is a block diagram of another image processing systemimplementing the present image compression method, in which the binarycompressed data stored in the memory 104 is accessed by image processingmeans 103, and then outputted to the host 105 for further processing,such as decompressing to recover the original image data. Since the datacommunication between image processing means 103, the memory 104 and thehost 105 is in the form of the binary compressed data, the transmissionamount of the image data between them is reduced, and the transmissiontime of the image data is therefore reduced.

With reference to the list of table I of FIG. 7 again, the recoveredimage data of a pixel with a low grayscale level is less distorted, andthe recovered image data of a pixel with a higher grayscale level ismore distorted. Therefore, a purpose for making the recovered image of ablack-area image, i.e. image with low grayscale levels, non-distorted,and the recovered image of a white-area image, i.e. image with highgrayscale levels, noise-eliminated, is obtained in accordance with thepresent image compression method of FIG. 3.

The embodiments are only used to illustrate the present invention, notintended to limit the scope thereof. Many modifications of theembodiments can be made without departing from the spirit of the presentinvention.

1. An image processing method for facilitating data transmission,comprising: capturing an image signal from an object with an imagecapture device; providing said image signal to an analog-to-digitalconverter for converting said image signal to X-bits binary digitalsignals, wherein X is a natural number; transmitting said X-bits binarydigital signals to image processing means for compressing said X-bitsbinary digital signals to a binary compressed data in the form ofn*2^(m), wherein X bits includes bit (X−1) to bit 0, m is a non-negativeinteger; when n is represented by the former Y bits of said X-bitsbinary digital signals, Y is a natural number, m is set to (X−Y), andthen m is represented by binary numbers with [log₂(X−Y+1)] bits, suchthat said X-bits binary digital signals are converted to said binarycompressed data represented by (m, n) with a sequence of [log₂(X−Y+1)]+Ybits, wherein m is the former [log₂(X−Y+1)] bits and n is the latter Ybits; and storing said binary compressed data represented by (m, n) withthe sequence of [log₂(X−Y+1)]+Y bits in memory means.
 2. The method ofclaim 1, wherein the step of compressing said X-bits binary digitalsignals to said binary compressed data in the form of n*2^(m), furthercomprising: (a) when bit (X−1) is logic level “1”, n is represented bythe former bit (X−1) to bit (X−Y) of said X-bits binary digital signals,m is set to (X−Y), and is represented by binary numbers with[log₂(X−Y+1)] bits, said binary compressed data is then outputted by (m,n) with the sequence of [log₂(X−Y+1)]+Y bits, wherein m is representedby the former [log₂(X−Y+1)] bits and n is the latter bits consisted ofsaid bit (X−1) to said bit (X−Y); (b) when bit (X−1) is logic level “0”and bit (X−2) is logic level “1”, n is represented by the former bit(X−2) to bit (X−1−Y) of said X-bits binary digital signals, m is set to(X−1−Y) and is represented by binary numbers with [log₂(X−Y+1)] bits,said binary compressed data is then outputted by (m, n) with[log₂(X−Y+1)]+Y bits, wherein m is represented by the former[log₂(X−Y+1)] bits and n is the latter bits consisted of said bit (X−2)to said bit (X−1−Y); (c) when bit (X−1) and bit (X−2) are logic level“0”, and bit (X−3) is logic level “1”, n is represented by the formerbit (X−3) to bit (X−2−Y) of said X-bits binary digital signals, m is setto (X−2−Y) and is represented by binary numbers with [log₂(X−Y+1)] bits,said binary compressed data is then outputted by (m, n) with[log₂(X−Y+1)]+Y bits, wherein m is represented by the former[log₂(X−Y+1)] bits and n is the latter bits consisted of said bit (X−3)to said bit (X−2−Y); (d) when each of bit (X−1) to bit (Y+1) is logiclevel “0” and bit Y is logic level “1”, n is represented by bit Y to bit1, m is set to 1 and is represented by binary numbers with [log₂(X−Y+1)]bits, said binary compressed data is then outputted by (m, n) with[log₂(X−Y+1)]+Y bits, wherein m is represented by the former[log₂(X−Y+1)] bits and n is the latter bits consisted of said bit Y tosaid bit 1; and (e) when each of bit (X−1) to bit Y is logic level “0”and bit (Y−1) is logic level “1”, n is represented by bit (Y−1) to bit0, m is set to 0 and is represented by binary numbers with [log₂(X−Y+1)]bits, said binary compressed data is then outputted by (m, n) with[log₂(X−Y+1)]+Y bits, wherein m is represented by the former[log₂(X−Y+1)] bits and n is the latter bits consisted of said bit Y−1 tosaid bit
 0. 3. The method of claim 1, further comprising accessing saidbinary compressed data from said memory means via said image processingmeans to a host and decompressing said binary compressed data to recoverto said X-bits binary digital signals.
 4. The method of claim 2, furthercomprising accessing said binary compressed data from said memory meansvia said image processing means to a host and decompressing said binarycompressed data to recover to said X-bits binary digital signals.
 5. Themethod of claim 3, wherein the step for decompressing said binarycompressed data comprises: (a) assigning the former [log₂(X−Y+1)] bitsof said binary compressed data to m, thereby obtaining the value of m,and assigning the latter Y bits of said binary compressed data to n; and(b) recovering said binary compressed data in the form of n*2^(m) tosaid X-bits binary digital signals.
 6. The method of claim 4, whereinthe step for decompressing said binary compressed data comprises: (b)assigning the former [log₂(X−Y+1)] bits of said binary compressed datato m, thereby obtaining the value of m, and assigning the latter Y bitsof said binary compressed data to n; and (b) recovering said binarycompressed data in the form of n*2^(m) to said X-bits binary digitalsignals.
 7. The method of claim 5, wherein when m is a positive integer,further comprising a step for compensating the pixel corresponding tosaid X-bits binary digital signals with a bit-enhanced method after thestep (b), wherein said bit-enhanced method comprises (c) calculating afirst average of a plurality of neighboring pixels around the pixel; and(d) calculating a second average of the first average and the pixel. 8.The method of claim 6, wherein when m is a positive integer, furthercomprising a step for compensating the pixel corresponding to saidX-bits binary digital signals with a bit-enhanced method after the step(b), wherein said bit-enhanced method comprises (c) calculating a firstaverage of a plurality of neighboring pixels around the pixel; and (d)calculating a second average of the first average and the pixel.
 9. Themethod of claim 1, further comprising accessing said binary compresseddata from said memory means by a host and decompressing said binarycompressed data to recover to said X-bits binary digital signals. 10.The method of claim 2, further comprising accessing said binarycompressed data from said memory means by a host and decompressing saidbinary compressed data to recover to said X-bits binary digital signals.11. The method of claim 9, wherein the step for decompressing saidbinary compressed data comprises: (a) assigning the former [log₂(X−Y+1)]bits of said binary compressed data to m, thereby obtaining the value ofm, and assigning the latter Y bits of said binary compressed data to n;and (b) recovering said binary compressed data in the form of n*2^(m) tosaid X-bits binary digital signals.
 12. The method of claim 10, whereinthe step for decompressing said binary compressed data comprises: (a)assigning the former [log₂(X−Y+1)] bits of said binary compressed datato m, thereby obtaining the value of m, and assigning the latter Y bitsof said binary compressed data to n; and (b) recovering said binarycompressed data in the form of n*2^(m) to said X-bits binary digitalsignals.
 13. The method of claim 11, wherein when m is a positiveinteger, further comprising a step for compensating the pixelcorresponding to said X-bits binary digital signals with a bit-enhancedmethod after the step (b), wherein said bit-enhanced method comprises(c) calculating a first average of a plurality of neighboring pixelsaround the pixel; and (d) calculating a second average of the firstaverage and the pixel.
 14. The method of claim 12, wherein when m is apositive integer, further comprising a step for compensating the pixelcorresponding to said X-bits binary digital signals with a bit-enhancedmethod after the step (b), wherein said bit-enhanced method comprises(c) calculating a first average of a plurality of neighboring pixelsaround the pixel; and (d) calculating a second average of the firstaverage and the pixel.